4006 papers
Condensed matter physics and materials science form a dynamic partnership, exploring how the collective behavior of atoms gives rise to the unique properties of solids and liquids. This field bridges the gap between fundamental quantum mechanics and the practical engineering of everything from flexible electronics to superconductors, turning abstract theories into tangible innovations that shape our daily lives.
At Gist.Science, we process every new preprint in this category directly from arXiv to make these complex discoveries accessible to everyone. Our team generates both plain-language overviews and detailed technical summaries for each paper, ensuring that researchers, students, and curious minds alike can grasp the latest breakthroughs without getting lost in dense jargon.
Below are the latest papers in condensed matter and materials science, organized by their most recent publication dates.
This study resolves long-standing discrepancies between diffraction and Raman spectroscopy in Ca0.4Sr0.6TiO3 by combining X-ray and electron microscopy to reveal that the high-temperature tetragonal phase retains nanoscale orthorhombic platelets with distinct local symmetry due to a loss of coherence in octahedral tilting.
This study employs pulsed nanocalorimetry to map the layer- and field-dependent magnetic thermodynamics of 2D CrSBr, revealing a dimensional crossover from bulk-like antiferromagnetism to intralayer ferromagnetism, a distinct odd-even layer parity effect, and the suppression of magnetic order by in-plane fields.
This paper presents a versatile digital twin for transmission electron microscopy that simulates electron beam trajectories and provides automated calibration tools to simplify complex lens alignment, enabling predictive setup of new imaging modes and facilitating AI-driven automation.
This paper predicts and theoretically characterizes a boundary Kerr effect in weakly doped zinc-blende semiconductors where a longitudinal electric field converts optically induced interband coherence into an edge-localized, helicity-odd polarization, providing a direct probe of multiband quantum kinetics without requiring spin-orbit coupling or intra-band accumulation.
This study demonstrates that ordered-to-disordered transfer learning with graph neural networks effectively predicts formation energies in high-entropy perovskite oxides but requires supplementary HEPO-specific data and three-body geometric representations to accurately model HOMO-LUMO gaps due to their sensitivity to local chemical environments.
This study employs first-principles calculations and maximally localized Wannier functions to investigate the electronic, phononic, and topological properties of the altermagnetic material CrSb, revealing that the anomalous Hall conductivity does not necessarily exhibit a linear relationship with magnetization, thereby challenging conventional classifications of magnetic materials.
This study characterizes the quasi-two-dimensional spin-1/2 antiferromagnet YCuGeO as a rare distorted triangular-lattice system where dominant further-neighbor exchange interactions and frustration prevent long-range magnetic ordering down to 0.4 K, instead fostering short-range correlations and a gapped field-polarized state above 2.6 T.
By employing an ultrahigh-sensitive ac magnetostrictive coefficient technique, this study revises the magnetic phase diagram of the quasi-2D material Cr2Te3, revealing complex phase coexistence, proposing a new canted ferromagnetic phase and a triple point, and highlighting decoupled magnetic ordering between specific Cr layers.
This study reveals that thermal annealing of the high-entropy alloy superconductor (TaNb)0.7(HfZrTi)0.5 tailors its microstructure to induce distinct vortex phases, including enhanced flux pinning and a unique two-phase superconducting state, by controlling the topological connectivity between phase-separated regions.
This paper demonstrates that a Gaussian process regression model (SALTED) trained exclusively on small displaced bilayer structures can accurately predict electron densities in large twisted bilayer moiré materials by utilizing long-range descriptors, thereby enabling efficient and reliable simulation of complex quantum phenomena like flat band formation and domain-wall electric fields that are otherwise computationally prohibitive.